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# Human Activity Recognition Edit

16 papers with code · Computer Vision

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# Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework

25 Feb 2020

Internet of Things (IoT) have widely penetrated in different aspects of modern life and many intelligent IoT services and applications are emerging.

# An Information-rich Sampling Technique over Spatio-Temporal CNN for Classification of Human Actions in Videos

6 Feb 2020

Traditionally in deep learning based human activity recognition approaches, either a few random frames or every $k^{th}$ frame of the video is considered for training the 3D CNN, where $k$ is a small positive integer, like 4, 5, or 6.

# Multi-label Prediction in Time Series Data using Deep Neural Networks

27 Jan 2020

In the most general setting of these types of problems, one or more samples of data across multiple time series can be assigned several concurrent fault labels from a finite, known set and the task is to predict the possibility of fault occurrence over a desired time horizon.

# Are Accelerometers for Activity Recognition a Dead-end?

22 Jan 2020

Overall, our work highlights the need to move away from accelerometers and calls for further exploration of using imagers for activity recognition.

# Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities

21 Jan 2020

In this study, we present a survey of the state-of-the-art deep learning methods for sensor-based human activity recognition.

# Motion Classification using Kinematically Sifted ACGAN-Synthesized Radar Micro-Doppler Signatures

19 Jan 2020

The synthetic dataset is used to train a 19-layer deep convolutional neural network (DCNN) to classify micro-Doppler signatures acquired from an environment different from that of the dataset supplied to the adversarial network.

# Classification of human activity recognition using smartphones

6 Jan 2020

Smartphones have been the most popular and widely used devices among means of communication.

# Improve Unsupervised Domain Adaptation with Mixup Training

3 Jan 2020

Unsupervised domain adaptation studies the problem of utilizing a relevant source domain with abundant labels to build predictive modeling for an unannotated target domain.

# Feature engineering workflow for activity recognition from synchronized inertial measurement units

18 Dec 2019

The ubiquitous availability of wearable sensors is responsible for driving the Internet-of-Things but is also making an impact on sport sciences and precision medicine.

# Template co-updating in multi-modal human activity recognition systems

4 Dec 2019

Multi-modal systems are quite common in the context of human activity recognition; widely used RGB-D sensors (Kinect is the most prominent example) give access to parallel data streams, typically RGB images, depth data, skeleton information.